Chad Babcock

Chad Babcock

University of Minnesota-Twin Cities

H-index: 12

North America-United States

About Chad Babcock

Chad Babcock, With an exceptional h-index of 12 and a recent h-index of 11 (since 2020), a distinguished researcher at University of Minnesota-Twin Cities, specializes in the field of geostatistics, forestry, remote sensing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Soil Organic Carbon and Wetland Intrinsic Potential, Hoh River Watershed, WA, 2012-13

Models to support forest inventory and small area estimation using sparsely sampled lidar: a case study involving g-liht lidar in tanana, alaska

Quantifying and correcting geolocation error in spaceborne LiDAR forest canopy observations using high spatial accuracy data: A Bayesian model approach

The FORest Carbon Estimation (FORCE) Project: Mapping GEDI-derived forest structure metrics in the US and Canada within a hierarchical spatial modeling framework.

Wildfires correlate with reductions in aboveground tree carbon stocks and sequestration capacity on forest land in the Western United States

An approach to estimating forest biomass while quantifying estimate uncertainty and correcting bias in machine learning maps

Cryptic carbon: The hidden carbon in forested wetland soils

Forest inventory using sparsely sampled LIDAR and NFI: A case study using G-LiHT LiDAR and FIA across Tanana, Alaska

Chad Babcock Information

University

Position

___

Citations(all)

454

Citations(since 2020)

352

Cited By

227

hIndex(all)

12

hIndex(since 2020)

11

i10Index(all)

13

i10Index(since 2020)

11

Email

University Profile Page

University of Minnesota-Twin Cities

Google Scholar

View Google Scholar Profile

Chad Babcock Skills & Research Interests

geostatistics

forestry

remote sensing

Top articles of Chad Babcock

Title

Journal

Author(s)

Publication Date

Soil Organic Carbon and Wetland Intrinsic Potential, Hoh River Watershed, WA, 2012-13

ORNL DAAC

A STEWART

M HALABISKY

C BABCOCK

D BUTMAN

DV D'AMORE

...

2024/4/24

Models to support forest inventory and small area estimation using sparsely sampled lidar: a case study involving g-liht lidar in tanana, alaska

Journal of Agricultural, Biological and Environmental Statistics

Andrew O Finley

Hans-Erik Andersen

Chad Babcock

Bruce D Cook

Douglas C Morton

...

2024/3/13

Quantifying and correcting geolocation error in spaceborne LiDAR forest canopy observations using high spatial accuracy data: A Bayesian model approach

Environmetrics

Elliot S Shannon

Andrew O Finley

Daniel J Hayes

Sylvia N Noralez

Aaron R Weiskittel

...

2024/1/8

The FORest Carbon Estimation (FORCE) Project: Mapping GEDI-derived forest structure metrics in the US and Canada within a hierarchical spatial modeling framework.

AGU Fall Meeting Abstracts

Daniel Hayes

Elliot Shannon

Chad Babcock

Andrew Finley

Sylvia Noralez

...

2021/12

Wildfires correlate with reductions in aboveground tree carbon stocks and sequestration capacity on forest land in the Western United States

Science of the Total Environment

Panmei Jiang

Matthew B Russell

Lee Frelich

Chad Babcock

James E Smith

2023/10/1

An approach to estimating forest biomass while quantifying estimate uncertainty and correcting bias in machine learning maps

Remote Sensing of Environment

Ethan Emick

Chad Babcock

Grayson W White

Andrew T Hudak

Grant M Domke

...

2023/9/1

Cryptic carbon: The hidden carbon in forested wetland soils

Anthony Stewart

Meghan Halabisky

Chad Babcock

David Butman

David D'Amore

...

2023/7/7

Forest inventory using sparsely sampled LIDAR and NFI: A case study using G-LiHT LiDAR and FIA across Tanana, Alaska

arXiv e-prints

Andrew O Finley

Hans-Erik Anderson

Bruce D Cook

Chad Babcock

Sudipto Banerjee

2023/2

Structural characteristics of black spruce (Picea mariana) infested with eastern spruce dwarf mistletoe (Arceuthobium pusillum), Minnesota, USA

Forest Ecology and Management

Ella R Gray

Matthew B Russell

Chad Babcock

Marcella A Windmuller-Campione

2022/11/1

Teal Carbon–Stakeholder-driven Monitoring of Forested Wetland Carbon

AGU Fall Meeting Abstracts

LM Moskal

Meghan Halabisky

Anthony J Stewart

David E Butman

Chad Babcock

...

2022/12

Using machine learning to improve predictions and provide insight into fluvial sediment transport

Hydrological Processes

J William Lund

Joel T Groten

Diana L Karwan

Chad Babcock

2022/8

Estimating Forest Carbon Using Machine Learning-produced Maps: Correcting for Machine Learning Estimator Bias and Estimating Uncertainty Using National Forest Inventory Data …

AGU Fall Meeting Abstracts

Ethan Emick

Chad Babcock

Andrew T Hudak

Andrew O Finley

Grant Domke

2022/12

Carbon in Minnesota’s Forests: Current Status and Future Opportunities

Matthew Russell

Christopher Edgar

Marcella Windmuller-Campione

R Lane Moser

Eli Sagor

...

2022/6/10

The Forest Carbon Framework: leveraging Earth-observation data to democratize carbon markets

AGU Fall Meeting Abstracts

Robert E Kennedy

Chad Babcock

David M Bell

David S Saah

Andrew T Hudak

...

2022/12

Cryptic carbon: wetland identification under perennial forest cover enhances spatially explicit modeling of soil carbon stock

AGU Fall Meeting Abstracts

Anthony J Stewart

Meghan Halabisky

Chad Babcock

David E Butman

David V D'Amore

...

2022/12

Joint Prediction of Forest Area and Forest Carbon using a Bayesian Hierarchical Spatial Modeling Framework

AGU Fall Meeting Abstracts

Chad Babcock

Audrey Hyke

2022/12

Using advanced airborne remote sensing as a sampling tool to support forest inventory in interior Alaska, USA

Hans-Erik Andersen

Jacob Strunk

Bruce Cook

Doug Morton

Mike Alonzo

...

2021/12/1

Improving Estimates of Wetland Carbon Beneath the Forest Canopy Through a Spatially Explicit Remote Sensing Approach

AGU Fall Meeting Abstracts

Anthony J Stewart

Meghan Halabisky

Chad Babcock

David Butman

David D'Amore

...

2021/12

Bias correction and uncertainty quantification of forest carbon maps using spatial regression models

AGU Fall Meeting Abstracts

Chad Babcock

Andrew Hudak

Ethan Emick

Robert Kennedy

2021/12

A Bayesian model to estimate land surface phenology parameters with harmonized Landsat 8 and Sentinel-2 images

Remote Sensing of Environment

Chad Babcock

Andrew O Finley

Nathaniel Looker

2021/8/1

See List of Professors in Chad Babcock University(University of Minnesota-Twin Cities)